Skip to main content
×
Home
    • Aa
    • Aa

Combining averting behavior and contingent valuation data: an application to drinking water treatment in Brazil

  • MARCIA A. ROSADO (a1), MARIA A. CUNHA-E-SÁ (a1), MARIA M. DUCLA-SOARES (a1) and LUIS C. NUNES (a1)
Abstract

This paper estimates WTP for drinking water quality in Brazil by combining averting behavior with contingent valuation data. Using bivariate probit models, alternative structures allowing for heteroscedasticity between and within data sources are incorporated by taking advantage of the different information content that characterizes each data source. We look at two covariates not yet examined in the literature when combining stated and revealed preferred data to explain the variance in the models: income and the bid in the contingent valuation questionnaire. Tests for parameter equality across data sets are performed. The results suggest that the specification of heteroscedasticity has a significant impact in WTP estimates and is crucial to legitimate the combination of data sets from different origins. The significant differences found in WTP between the two sources are discussed.

Copyright
Corresponding author
Correspondence to: Email: mcunhasa@fe.unl.pt
Footnotes
Hide All
We thank two anonymous referees for valuable comments. We acknowledge the financial support from FCT-POCTI/ECO/36660/2000.
Footnotes
Recommend this journal

Email your librarian or administrator to recommend adding this journal to your organisation's collection.

Environment and Development Economics
  • ISSN: 1355-770X
  • EISSN: 1469-4395
  • URL: /core/journals/environment-and-development-economics
Please enter your name
Please enter a valid email address
Who would you like to send this to? *
×

Metrics

Full text views

Total number of HTML views: 0
Total number of PDF views: 20 *
Loading metrics...

Abstract views

Total abstract views: 114 *
Loading metrics...

* Views captured on Cambridge Core between September 2016 - 25th May 2017. This data will be updated every 24 hours.